Please use this zoom link for the event.
Please join us for a UW Data Science Seminar event on Tuesday, October 19th from 4:30 to 5:30 p.m. The seminar will feature Associate Professor Katie Shilton and Postdoctoral Scholar Emanuel Moss from the University of Maryand’s College of Information Studies (iSchool).
“Trustworthiness in Social Data Science: Excavating Awareness and Power”
Abstract: Data science researchers using data about people face a significant challenge: we largely don’t agree on norms or practices for ethical and trustworthy social data science research. Our presentation, based on the work of the collaborative PERVADE project, will highlight two entwined trust problems: participant unawareness of such research, and the
relationship of social data research to corporate datafication and surveillance. We will suggest a way to address these problems inspired by a research method which has also struggled with the trustworthiness of its practices: ethnography. To grapple with the colonial legacy of their methods, ethnographers have developed analytic lenses and researcher practices that foreground relations of power and participant awareness. We will discuss ways that pervasive data researchers can incorporate reflection on awareness and power into their research to support the development of trustworthy social data science.
Katie Shilton is an associate professor in the College of Information Studies at the University of Maryland, College Park. Her research explores ethics and policy for the design of information technologies. She is the PI of the PERVADE project, a multi-campus collaboration focused on big data research ethics. Other projects include participatory design to support automated tools for online content moderators; tracing the influence of privacy discourse in the media and among policymakers; analyzing ethical cultures in computer security research; and understanding and encouraging ethics discussions in mobile application development. Her work has been supported by a Google Faculty Award and multiple awards from the U.S. National Science Foundation. Katie received a B.A. from Oberlin College, a Master of Library and Information Science from UCLA, and a Ph.D. in Information Studies from UCLA.
Emanuel Moss is a joint postdoctoral scholar at Cornell Tech’s Digital Life Initiative and Data & Society Research Institute’s AI on the Ground Initiative. He has written extensively on issues of fairness, accountability, ethics, and governance for AI systems, as well as algorithmic impact assessment practices. He was previously a research assistant on the Pervasive Data Ethics for Computational Research (PERVADE) project. Emanuel is broadly interested in investigating machine learning from an ethnographic perspective and studying the role of data and computer scientists as producers of knowledge. Emanuel holds a BA from the University of Illinois, an MA from Brandeis University, and a PhD in Anthropology from the CUNY Graduate Center. He has previously worked as a digital and spatial information specialist for cultural heritage and environmental impact assessment projects throughout the United States.
The UW Data Science Seminar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data science, such as the sciences, engineering, humanities and arts along with methodological areas in data science, such as computer science, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional partners, governmental agencies and industry.
The 2021-2022 seminars will be hybrid virtual and in-person events, and are free and open to the public.